Modular ontology modeling

IF 3 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Semantic Web Pub Date : 2022-05-20 DOI:10.3233/sw-222886

C. Shimizu, K. Hammar, P. Hitzler

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引用次数: 18

Abstract

Reusing ontologies for new purposes, or adapting them to new use-cases, is frequently difficult. In our experiences, we have found this to be the case for several reasons: (i) differing representational granularity in ontologies and in use-cases, (ii) lacking conceptual clarity in potentially reusable ontologies, (iii) lack and difficulty of adherence to good modeling principles, and (iv) a lack of reuse emphasis and process support available in ontology engineering tooling. In order to address these concerns, we have developed the Modular Ontology Modeling (MOMo) methodology, and its supporting tooling infrastructure, CoModIDE (the Comprehensive Modular Ontology IDE – “commodity”). MOMo builds on the established eXtreme Design methodology, and like it emphasizes modular development and design pattern reuse; but crucially adds the extensive use of graphical schema diagrams, and tooling that support them, as vehicles for knowledge elicitation from experts. In this paper, we present the MOMo workflow in detail, and describe several useful resources for executing it. In particular, we provide a thorough and rigorous evaluation of CoModIDE in its role of supporting the MOMo methodology’s graphical modeling paradigm. We find that CoModIDE significantly improves approachability of such a paradigm, and that it displays a high usability.

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模块化本体建模

为了新的目的重用本体，或者使它们适应新的用例，通常是困难的。根据我们的经验，我们发现这种情况有以下几个原因:(i)本体和用例中的表示粒度不同，(ii)潜在可重用本体缺乏概念清晰度，(iii)缺乏良好建模原则的遵循和困难，以及(iv)缺乏重用重点和本体工程工具中可用的过程支持。为了解决这些问题，我们开发了模块化本体建模(MOMo)方法，以及它的支持工具基础设施，CoModIDE(综合模块化本体IDE -“商品”)。MOMo建立在已建立的极限设计方法的基础上，并且像它一样强调模块化开发和设计模式重用;但关键是增加了图形模式图的广泛使用，以及支持它们的工具，作为从专家那里获取知识的工具。在本文中，我们详细介绍了MOMo工作流，并描述了执行它的一些有用资源。特别是，我们对CoModIDE在支持MOMo方法的图形建模范式方面的作用进行了全面而严格的评估。我们发现CoModIDE显著地提高了这种范例的可接近性，并且显示出很高的可用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

8.30

自引率

6.70%

发文量

期刊介绍： The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.